Generally, database management systems store information in a highly organized manner. The information is stored in tables which represent groups of related data. The tables may be indexed (referenced) by one or more indices. These indices permit the database application to rapidly search for and access the information stored in the tables. In many databases, a single entity can have several different tables of data which may or may not be indexed by the same index. For example, in a human resources database, each employee can have a table that stores employee information (such as start date, leaves of absence (LOA), grade changes, department changes, etc.) and a table that stores department information for the employee (this can include the departments that the employee has been a member of, department identifiers, department descriptions, etc.). These two tables, which are used to store information for a single entity (for example, an employee) are often indexed using the effective date. Examples of the effective date may be the date of hire of the employee or the date of a promotion, etc.
When data related to a single entity is spread out across multiple tables, it can become difficult to merge all of the information regarding that entity and then produce a meaningful report about the entity without needing to perform a great deal of processing. In the human resources database above, for example, with the employee information and department information spread across two tables, it can be difficult to produce a report that would reflect the entities organizational changes over time. Additionally, some personal information, such as termination/hire, leave of absence, etc., may be hard to exclude.
Post processing can eliminate data that is to be excluded. For example, the data can be searched for instances related to termination, hire, leave of absence, etc., and these instances can be removed from a report prior to the report being produced in final form. Additionally, post processing can be used to provide information from other tables.
While additional processing (either by computer or by hand) can be used to provide (or exclude) the information, it would be more efficient if the information can be extracted from the tables without needing any post processing from man or machine.
One disadvantage of the prior art is that post processing is inefficient and requires additional processing steps by either man or machine to produce the desired information. This can greatly increase the amount of time and costs needed to produce reports.
A second disadvantage of the prior art is that data that is spread across multiple tables, but indexed by the same index is generally not easily combined and extracted without requiring (again) post processing.